1. Field of the Invention
The present invention relates to a color descriptor data structure for a color device, the color descriptor data structure containing a reference boundary descriptor representing reference colors of the color device, a plausible boundary descriptor representing plausible colors of the color device which include a whitest-white color and a blackest-black color, and a neutral color descriptor representing neutral colors of the color device which extend in range from the whitest-white color to the blackest-black color.
2. Description of the Related Art
The use of gamut mapping algorithms in the field of graphic arts is known, and they are used to reproduce an image which was rendered by an input device on an output device, where the input device and the output device typically have different gamut boundaries with respect to each other. In other words, the gamut of colors that can be reasonably reproduced by the input device is typically not the same as the gamut of colors that can be reasonably reproduced by the input device. In such a situation, the gamut boundaries of the two devices are different, and so gamut mapping is used to render the image from within the input device gamut boundary to within the output device gamut boundary, so as to more accurately reproduce the color image on the output device.
Gamut mapping of image data from one gamut boundary to another in the graphic arts field is typically performed using a gamut mapping algorithm which is a particular method of mapping color data between gamut boundaries. In addition, the gamut mapping often uses gamut boundary descriptors for both the input and the output device in order to obtain a reference between the two gamut boundaries for appropriate gamut mapping of the image.
When gamut mapping a rendered picture of an input medium, such as a developed print on photographic paper or a magazine picture, to an output medium on an output device, the white point and the black point of the input medium are typically mapped to the white point and the black point of the output medium. The colors between the white point and the black point of the input medium are then mapped to fall between white point and the black point of the output medium. In the case that the rendered picture on the input medium includes a whitest-white, such as light reflecting off of a chrome bumper or such as a light bulb, and a diffuse white, such as a white shirt, the whitest-white is generally mapped to the white point of the input medium, and the diffuse white is mapped to a neutral color of the input medium which is darker than the medium's white point. In this manner, the range of “whites” of the rendered photograph fall between the white point and the black point of the input medium. In this example, the whitest-white represented at the white point of the input medium is mapped to the white point of the output medium, and the diffuse white at the particular neutral point of the input medium is mapped to a particular neutral point of the output medium. In such a case, the white points and the particular neutral points of the input medium and of the output medium are often not the same.
Gamut mapping becomes more difficult when using an unrendered picture from an input device such as a camera or a video camera. In such cases, the whitest white point of the photographed scene, such as a specular white, an emissive white, or a diffuse white, is not necessarily mapped to the white point of the input medium, such as a photographic film, videotape, or digital media. Neither is the blackest point of the photographed scene necessarily mapped to the black point of the input medium. This present problems when gamut mapping the unrendered picture from the input device, such as a camera, to an output medium in an output device, such as a printer, primarily because it is not known at the time of mapping where the whitest-white points and the black points of the unrendered picture fall on the input medium with respect to the white point and the black point of the input medium.
Input media such as photographic film and digital video provide “headroom” to render portions of the scene falling between “white with detail”, such as diffuse white, and “white without detail” such as specular white. Similarly, photographic film and digital video also provide “footroom” to render portions of the scene falling between “black with detail”, such as shadow black, and “black without detail”, such as blackest-black. In the video industry, a standard encoding is used to represent colors of the scene. Such a standard encoding is the ITU 709 specification in which luminance (Y), which depicts whiteness, is encoded in 8 bits, thereby allowing values between 0 to 255. In this standard, reference black is encoded at a luminance value of 16, and reference white is encoded at a luminance value of 235, thereby leaving the range between 236 and 255 to represent specular highlights and emissive sources.
The video industry is generally based on reference devices and standardized encoding. This means that gamut boundary information of a particular video device is not needed for rendering of an image from the particular video device on another video device because all video images are encoded for reproduction on the same standardized reference device. Unfortunately for the graphic arts industry, when it is desired to reproduce an unrendered image from a particular video device on an output device such as a printer, optimal tonal mapping is difficult, if not impossible. One problem is that the gamut mapping is not provided with information about the location of whitest-white and diffuse white with respect to the white point of the input medium, and is not provided with information about the location of blackest-black and shadow black with respect to the black point of the input medium. Neither is the gamut mapping provided with information about the location of various tonal gray points falling between blackest-black and whitest-white on the input medium
In addition to the above-mentioned problems with gamut mapping during the reproduction of unrendered photographic and video images onto an output device with a different gamut boundary, photographic and video devices produce gray colors which do not necessarily fall on the neutral axis of the color appearance model in which can be used to depict the color gamut of the photograph and/or video device. A typical color appearance model is in CIECAM02 JCh color space, and so gray colors of the photograph and/or video device may not necessarily fall on the J axis, where chroma (C) has a zero value. This representation of gray colors in the color appearance model for photographic and/or video devices is very problematic for gamut mapping algorithms which expect gray colors to fall directly on the J axis, where chroma (C) has a zero value.
Accordingly, it is desirable to find a solution to one or more of the foregoing problems. In particular, it is desirable to be able to adequately describe the range of colors of a source input device that fall between reference colors, such as diffuse white, and plausible colors, such as whitest-white, of the source input device, and to adequately describe the location of the gray colors of the source input device.